Display and analysis of medical images using calibrated pixel values in units of known properties of reference materials

ABSTRACT

Methods to calibrate and display medical images with pixel values with known properties of one or more reference materials provide images which allow more accurate quantification of certain tissue properties. The images provide advantages in medical diagnosis by being standardized and independent of imaging devices or imaging techniques. The images are automatically displayed and/or filmed in optimum windows and levels. The images are calibrated with a variety of reference materials and displayed in a variety of measurement units. For example, CT images are displayed with pixel values in units of grams per cubic centimeter calibrated to a known reference which relate to but are quantitatively different from the customary Hounsfield scale based on water as the reference material. A novel more quantitative CT image display scale provides advantages in diagnosis, image recording and standardization. References with known magnetic properties imaged with MRI provide calibration and display standardization.

RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.11/296,936, filed on Dec. 8, 2005, which is a continuation of U.S.patent application Ser. No. 09/989,995, filed on Nov. 21, 2001 (now U.S.Pat. No. 6,990,222), the entireties of which are hereby incorporatedherein by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention is in the field of medical imaging usingcomputerized tomography (CT), and in particular, is directed to a methodto determine tissue densities in the body of a subject and to providecalibrated display of images.

2. Description of the Related Art

CT scanners have become a major diagnostic modality in modem medicineand are widely used for many types of exams. Most exams are performed bysubjective viewing of the cross-sectional images on either film orelectronic displays. This subjective viewing makes use of assumedquantitative image pixels, which define boundaries of tissues, organs orforeign masses, and subjective discrimination of tissue types by densitydifferences. Identification of diagnostic details is fundamentallydependent upon the detection of image detail edges.

Measurements of true tissue densities in the living subject have manydiagnostic benefits, in addition, to bone densitometry. Several new andpromising measurements include lung nodule density, cardiaccalcifications, aortic calcifications, soft plaque, fat measurements,BMI, lung volume and density, liver iron content, and the like.Knowledge of true tissue densities will allow diagnostic analysis ofimages not currently possible. Absolute change in CT numbers may allownew diagnostic criteria. Emphysema, tissue fat content, calcifications,liver iron build up, and the like could be determined from thecalibrated data, thus, adding a new dimension to CT interpretation.

Radiologists routinely make subjective, and even quantitativemeasurements of foreign masses, tissues or organs by manually placingcursors to define the 2-D extent of the target. If the window and/orlevel (brightness and contrast) are changed in the display, the apparentsize of the target changes because the boundary is not discrete and ismoved in or out of the display range. The measured object size is, thus,frequently inaccurate, and will vary from operator to operator and fromscanner to scanner depending on the display conditions and scannerproperties.

CT images are filmed by a technologist or other operator and arerecorded on standard x-ray film for light box viewing. The size, andapparent density of target objects, and foreign masses depend on thewindow and level settings. The window/level settings are subjectivelyset for filming and display of a particular image. In addition, theprocess to set and adjust the window and level requires operator timeand is currently very inefficient. Electronic image data are frequentlyerased, and only the films retained for the medical records. Laterviewing is limited to the subjective display and/or the filming levelspreviously chosen by the operator.

The foregoing discussion is based on the assumption that pixels and/orvoxels of the image are a representation of the true underlying densityof the target tissue. Although this assumption is roughly maintained dueto the scanner being calibrated to water and air, it is sufficientlyinaccurate that many quantitative measurements cannot be made with eventhe best modern scanners.

There has been significant, recent interest in quantifying coronarycalcium, as well as calcifications in the aorta, lungs, breast, andcarotids. It is desirable to provide improved calibration methods forall the tissues of the body. Whole body CT scanning is growing rapidlyin use. The entire torso is scanned creating many thin slices foranalysis and viewing. The radiologist attempts to subjectively analyzemany structures from many images, which is laborious and very timeconsuming. Measurements of densities and volumes of many organs are ofinterest, including heart, lung, liver, kidneys, prostate, thyroid,pancreas, and the like. Quantitative measurements of calcifications, ofareas and volumes, as well as standardized viewing and filming ofimages, all require improved calibration methods.

CT scanners have been used as quantitative instruments for bone densitymeasurements in quantitative computerized tomography (QCT) by the use ofcalibration phantoms. More recently, fast CT scanners, such as theImatron EBCT and GE Light Speed, have been used for coronary calciumanalysis with or without phantom calibration. Several calibrationapproaches have been used in QCT bone densitometry includingsimultaneous phantom calibration with bone and tissue equivalentphantoms, non-simultaneous calibration with more anthropomorphicphantoms, non-phantom calibration using histogram analysis of fat andmuscle regions, simultaneous phantom calibration with blood samplecorrections, and dual energy calibration to correct for vertebral fat inbone density measurements. These approaches have been developedspecifically for and used for QCT bone densitometry of vertebraltrabecular bone.

CT numbers, (Hounsfield Units, HU), are estimates of the attenuationcoefficients of tissue relative to water as the calibration referencematerial. However, CT numbers fail to be truly quantitative for severalreasons. For example, the tissue attenuation coefficients are photonenergy dependent, and the x-ray beam energy spectra are not measured orknown for individual patients. Further, there exists many beam energyspectra in each CT slice, i.e., a unique spectrum for each path lengththrough the patient, and seen at a particular detector element, and aunique spectrum for each view through the patient. The beam spectrumchanges with the thickness and composition of tissues in the pathlength. The quantities of fat, soft tissue, air, and bone vary with eachprojection. X-ray tube filtration to shape the beam intensity alsochanges the beam spectrum resulting in variation in CT numbers based onlocations within the field of view. Image processing software andcurrent beam hardening corrections have as an objective to improvesubjective image quality, and do so, often, at the expense ofquantitative information. CT number calibrations and beam hardeningcorrections are based on idealized phantoms, which are often circular inshape and composed of water, plastics, or other synthetic materials.These differ significantly from the shape and composition of realpatients. CT numbers at the edge of the field of view, where acalibration phantom would be placed, are different from those inside thepatient. This produces errors in calibration since the phantom can neverbe placed inside the body cavity. CT numbers vary through the image oneach slice, and are dependent on table height, position in the beam,slice thickness, field of view, and sometimes even the time of day asthe scanner warms up.

Many diagnoses are based subjectively on perceived tissue densities andregional changes in density as demonstrated by the CT numbers in theimage. Results currently are independent of patient variability and CTequipment. Standardization and calibration of the CT numbers acrossdifferent patients and CT scanners will aid in interpretation of manyconditions.

It is frequently desirable to make quantitative measurements from bothtwo-dimensional (2D) and three-dimensional (3D) data sets in medicalimaging. Accurate measurements of organ or tumor volumes andcross-sectional areas of various biological details, such as bloodvessels, all have potential medical diagnostic value. Quantification ofvascular calcium and micro calcifications throughout the body isvaluable in cardiovascular disease and breast cancer detection, forexample. All of these tasks use gray scale, voxel-based data. Theidentification of the edge of a target region may use any of severaledge detection algorithms, such as the Sobel operator in either 2D or 3Dspace. This prior art has used image voxels as outputted from theimaging device, i.e., CT scanner, digital radiography apparatus,magnetic resonant scanner (MRI) or mammography system. In all cases, theimage data was not calibrated. Since the image gray scale values varywith the imaging conditions and subject properties, the definition of anedge also varies.

In some cases, the diagnostic detail is defined by a pre-selectedthreshold value, i.e., if the target element equals or exceeds thethreshold value, the detail is counted as a positive diagnostic find.Coronary artery calcifications are a notable example. With currentlyavailable CT scanners, calcifications that exceed either 130 HU or 90 HUare counted as positive finds. The Hounsfield units (HUs) are known tovary with scanner type, x-ray beam energy, reconstruction software,patient size and composition, and the like. As a result, the thresholdvalue varies depending on these conditions. A positive calcificationfind is thus different for a small female versus a large male. If apatient is scanned on one scanner and scanned later on a second scannerfor a follow-up exam, the results will be different. The diagnosticresults are therefore dependent upon several variables of the imagingsystems, as well as being dependent on the patients.

The use of external calibration phantoms containing bone equivalentsamples have been used for some time in QCT Bone Densitometry. Suchphantoms have greatly aided the standardization accuracy andreproducibility of bone density measurements. In this case, however, thetarget tissue, bone, is large, of a high density much larger than softtissue, and located relatively close to the calibration phantom.

The use of external calibration phantoms has only recently beenattempted with coronary calcium quantification. Calibration phantomshave not been used for soft tissue density measurements or for physicaldimensional measurements. One of the problems which exists withquantitative CT relates to the variation of image gray scale valuesthroughout the area of the image. The same tissue type located in onelocation within the body may produce a different Hounsfield unit valueversus a different location. That is, the image is not homogeneousthroughout. Not only does the image vary in intensity, but it alsovaries in effective beam energy. As a result, no one unique calibrationcurve is available for each CT slice or for a complete digital 2Dradiograph. The situation is complicated by being dependent upon theposition of the object within the scan field, device servicing andcalibrations, and x-ray tube wear.

SUMMARY OF THE INVENTION

Unlike prior art devices in which image data was not calibrated, thedisclosed invention presents a method to calibrate the image data suchthat a calibrated image detail edge can be quantitatively defined,located and relocated on follow up images. The reproducibility ofphysical measurements of target volumes, areas, and distances is greatlyimproved.

The embodiments of the present invention provide a method to calibratethe image to produce consistent and standardized results, independent ofthe measurement conditions discussed above (e.g., scanner type, beamenergy, reconstruction software, patient size and composition, and thelike). Clinical results will be more consistent, more accurate, and moreprecise. The ability to follow patients on follow-up exams to monitordisease progress will be greatly benefited.

The density differences in Hounsfield unit values between the softtissues of the body are small, compared to bone density, and they aremore difficult to measure. Microcalcifications in the vascular system ofthe body produce small density differences as well, and are difficult tomeasure reproducibly. The embodiments of the present invention overcomethe small differences in the density of soft tissue ormicrocalcifications to facilitate measurements throughout the body, bothin areas near the external phantom and in areas distant from theexternal phantom to overcome the inadequacies of the conventionalmethodology of QCT calibration with an external phantom. In particular,the embodiments of the present invention enable a method to quantifyx-ray images that uses a hybrid calibration method that overcomes theselimitations.

Filming and viewing CT images can be automated and presented in aquantitative way, which further aids the interpretation. Standardizationof filming windows and levels to an absolute scale based on true densityprovides consistent viewing conditions. Accurate and reproduciblefilming could be automated and standardized to quantitative valuesconsistent through the medical community.

The body is always in a state of homeostasis, attempting to keep thebody in a static and stable condition. Indeed, if some tissues of thebody change by even small quantities, life may be challenged. Blood isthe fluid of life, and must be maintained within relatively narrowranges. It is therefore a very consistent substance, both in individualpatients, and from patient to patient. The literature on bloodcomposition from the standpoint of effects on physical density showsthat blood density and the resulting CT HU values do vary with thehematocrit, red cell volume, iron content, blood fats, and hydration,but these variations are small compared to the required calibrationaccuracy. This analysis indicates that these variations are acceptablefor the disclosed invention. Biologic variations in blood density areexpected to generally produce a range of variation of ±2 HU and torarely exceed ±4 HU.

Since blood is always homogeneously mixed and consistent throughout eachindividual body, the blood provides for a unique and consistent in vivocalibration tissue. Since blood in the great vessels and heart iscentrally located within the body, the position of such blood is idealas an internal surrogate calibration tissue. The embodiments inaccordance with the present invention provide a method that uses bloodfor tissue calibration in x-ray imaging systems, both when used with anexternal calibration phantom and when used without an externalcalibration phantom.

Air calibration is frequently used in CT scanner calibration along withwater. The Hounsfield unit value of air is defined as the minimum CTdensity, usually −1000 HU. Air density is used for quality assurance androutine calibration-file setup of the scanner. Air calibration has notbeen used as a calibration reference with individual patient scans. Itcan be assumed that air is a consistent and reproducible substance.Scatter radiation degrades images by adding a DC image component, whichreduces image contrast, signal-to-noise ratio, and dynamic range. Themeasurement of tissue densities and target edges are degraded. The airpresent within the esophagus provides an internal air reference forcalibration in cardiac and chest imaging. Bowel gas provides a potentialair reference for the abdomen. The air adjacent, but outside the body inthe environment, provides an external air reference. The embodiments inaccordance with the present invention provide a method to use bothinternal air and external air as calibration references in tissuedensity measurements.

Prior art has disclosed methods to use muscle and visceral fat withhistogram analysis to provide calibrations without an external phantomfor QCT bone densitometry (See, for example, U.S. Pat. No. 5,068,788 toGoodenough). Muscle and visceral fat always have mixtures of both tissuetypes, muscle and fat, but the technique proposes that the histogrampeaks can be made to represent each tissue type as calibration points.It would be helpful to have a tissue which contains fat without muscleintermixed. This does occur, but, unfortunately on the exteriorcircumference of the body as subcutaneous fat.

Segmentation techniques are now available to isolate these fat tissues.The thin or not so thin layer of subcutaneous fat can be defined andisolated with modem segmentation techniques. The location of the fattissue, within the scan field and relative to the target organ, can bemeasured. Since the fat is distributed around the subject, the fat canbe used to make corrections for beam hardening and scatter. The presentinvention discloses a technique for using subcutaneous fat as a knownreference tissue for calibration in tissue density measurements with aCT scanner.

One aspect of the embodiments in accordance with the present inventionis a method to calibrate CT images. The method utilizes both an exteriorfixed calibration phantom with known samples of tissue equivalentmaterials, and which also uses an interior sample of tissue of thepatient. The exterior calibration phantom has multiple samples ofvarying densities, varying compositions, or varying densities andvarying compositions, which provide a common standard of reference thatis consistent for all scanners. The phantom sample readouts provide aregression equation which has a slope that provides a measure of theeffective beam energy of the CT scanner for that particular patient. Thephantom samples run substantially along the torso of the patient, andthe samples are included in each CT slice with simultaneous scanning.The calibration offset, the y-axis intercept, is determined from thepatient's own tissue, preferably heart tissue and/or blood. The totalheart is segmented in 3D space, and a best representation of the averagevoxel HU value is determined. Calcifications and fat are removed fromthe volume by thresholding and by histogram analysis. The calibrationmakes the assumption that blood density is consistent, and the same forall people. Although blood density does vary with hematocrit, blood cellvolume, and iron content, these variations are relatively small andacceptable. Human blood, and heart tissue are remarkably similar in allsubjects. In addition, the embodiments of the present invention make useof the assumption that blood is homogeneous and has a constant densityin every subject, which allows calibrations using the heart and greatvessels.

A hybrid calibration equation is created for each CT slice, and thuseach region of the body is calibrated with data from that region. Theblood and heart tissue become an additional in vivo phantom sample,which is homogeneous and is dispensed throughout the body. The hybridcalibration is applied to all image pixels of all slices to generate anew data set, which is now calibrated and standardized.

Absolute thresholds and standard edge detection algorithms are appliedto the calibrated images to measure volumes, areas, and distances. Organor tumor mass can be readily measured in a reproducible manner, forexample: Absolute and quantitative display ranges, window and level, areset as default values on electronic displays and for filming. Optimumand standardized viewing conditions can be readily maintained for moreconsistent diagnosis.

The calibration methods disclosed herein can be readily applied on allCT scanners and on all tissues of the body with accurate andreproducible results while reducing operator time. Any tissue in thebody can be calibrated including lung, heart, kidney, bone,calcifications, plaque, and the like.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a cross-sectional image through the heart with anexterior calibration phantom, in accordance with an embodiment of thepresent invention.

FIG. 2 illustrates hybrid calibration curves at different bodylocations.

FIG. 3 illustrates a histogram of the HU values of the segmented heartvolume showing the mode which is used for the calibration method of thepresent invention.

FIG. 4 illustrates the gray scale values at the edges of a tissue detailand the influence of display window and level on the location of theperceived edges and size of the detail.

FIG. 5 shows histogram plots of 4 ROI positioned in air outside andaround the body of a patient.

FIGS. 6A and 6B illustrate a flow chart that represents thecomputational procedure of the hybrid calibration method.

FIG. 7 illustrates a cross sectional image of the abdomen with referencecalibration phantom in place.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT

A preferred embodiment of the present invention is described below inconnection with the flow chart of FIGS. 6A and 6B in view of theillustrations in FIGS. 1-5.

As illustrated by a step 110 in FIG. 6A, a CT scan of the subject isfirst taken with the subject lying on the reference calibration phantom.Several CT images are taken in a short time period. Preferably, CTimages are taken using a multi-slice spiral scan CT scanner or using theEBCT Imatron scanner, although any CT scanner can be used for manytissues. Scans of the heart for coronary calcium analysis will requirefast scan times to stop the motion of the beating heart.

After reconstruction of the CT images in the scanner computer, a firstcross-sectional image of the subject is displayed in a step 112 in FIG.6A. FIG. 1 illustrates a representative depiction of such an image takenthrough the heart showing coronary calcium 6. The heart tissue 2, theaorta 3, the lung 4, the chest wall and a reference phantom 5 are shownin FIG. 1. The reference calibration phantom 5 includes threerepresentative samples (S1, S2, and S3) of varying densities. A priorart automated algorithm is used preferably to find the calibrationphantom in the image as shown in FIG. 1, and to placeRegions-of-Interest (ROIs) within each phantom sample, as illustrated bya step 113 in FIG. 6A. An exemplary prior art algorithm is illustratedin U.S. Pat. No. 4,922,915 to Arnold, which is incorporated by referenceherein.

The phantom samples contain known sample densities (Sd) and produce ROImean CT numbers (HU_(s)) for each sample. For example, sample S₁ maypreferably contain water density or 0 concentration of the calibrationadditive material. The calibration additive material is advantageously acalcium containing material such as calcium hydroxyapatite in a solidwater equivalent synthetic material.

In a step 114, the phantom measurements are expressed in a regressionequation of the form y=I_(o)+S×HU_(s). The slope, S, of the regressioncurves is related to the effective beam energy used to make the image.For different KVps, filtration of the primary beam, and differentpatient sizes and compositions, the slope will vary. The intercept,I_(o), of the regression equation is a measure of the CT number of thewater density sample. The slope, S, will vary with location in a givenpatient due to differing amounts and densities of tissue being presentin the beam. FIG. 2 is a depiction of three regression equations showingdifferent slopes for 3 regions of the body. These regions could bedifferent cross sectional areas and/or different body compositions offat, muscle or bone. The regression slope will also vary with CT scannermodel and calibration.

The reference tissue region is next located in a step 115. The referencetissue may be blood, the heart filled with blood, subcutaneous fat,internal or external air. Preferably the heart and blood are used incoronary calcium analysis. Other tissue may be preferable in otherexams. These tissue regions may be located by making use of theirlocation and expected CT number range and their location relative to thelocation of the calibration phantom. The operator may place a cursormarker within the reference tissue as a seed point. The software thenuses region growing techniques to find the region boundaries.

After either automatic location or manual location, the measuringanalysis steps can be applied. One or multiple reference tissues may beused in the calibration. If the reference tissue is the heart and blood,the algorithm identifies the blood filled heart which is surrounded bylung tissue. The location step is aided by first finding the aorta andthe inferior margins of the heart, which may be positioned in contact oradjacent to the diaphragm, the liver or both. The operator may need insome cases to place a cursor marker to aid in this boundary distinction.

In a step 116, the regression equation is applied to the entire image,or, in some cases, may be applied to only the reference tissue regionplus additional surrounding tissue. This step provides an improveddefinition of the reference tissue boundaries. Alternatively, theregression equation may not be applied to the image or reference tissueregion. The methodology will work without this optional step.

In a step 117, the regression equation is used to define a quantitativevalue as the specific edge. By using calibration, the boundaries of thereference tissue can be reproducibly located and relocated with fixedcriteria. This edge definition and calibration is not to be confusedwith the calibration step which defines the edge of the target tissuethat will be discussed below.

The voxels within the boundaries of the reference tissue are next usedto calculate a histogram in a step 118. A representative histogram ofthe heart as reference tissue is shown in FIG. 3.

The histogram is smoothed and a Gaussian curve is fit to the peak.Several neighboring slices may be scanned at this point in a step 119.The ends of the histogram may be filtered to remove unwanted voxelreadings not representative of blood. Then, in a step 120, a backgroundlevel due to scattered radiation or surrounding tissue, which can bedistinguished from the reference tissue, may be subtracted. FIG. 5 showschanges in scattered radiation outside and adjacent to the body. ROIswere positioned in air and the histogram plotted of the pixel values ofthe ROI. With correct air calibration and no scattered radiation, theROI should produce HU values around −1000. The modes of the plotsproduce values of −964, −980, −987 and −994. These measurements showdifferences from expected values of 6 to 36 HU, which differences dependon location. Similar measurements can be made on air within the body.

The mode of the Gaussian fit is next calculated in a step 121. Thecalculated mode is next combined with the phantom regression equation tocreate the final hybrid calibration equation in a step 122. Thecalibration equation is an expression of the form:T _(d)=(HU _(b) −HU′ _(b))+S×HU,where T_(d) is the tissue density of the target tissue or organ to beanalyzed. T_(d) may be expressed as corrected HU values or T_(d) may berepresented in tissue density units such as grams per cubic centimeter(g/cc). HU_(b) is the previously determined or known CT number ofrepresentative blood, i.e., the known blood density or HU values ofblood determined in vitro under similar scanning conditions. Bloodsamples from representative patients are placed in a container andscanned inside a tissue-like phantom, while maintaining temperaturesrepresentative of the human body, and scanning conditions representativeof the clinical scans. HU′_(b) is the measured reference tissue densitywhich in this example, is the mode of the histogram of the heart andblood. S is the slope of the regression equation measured from thecalibration phantom samples. HU is the scanner CT number or may be a CTnumber measure of the target tissue to be analyzed. Note that the targettissue may be coronary calcifications, an organ, an unknown mass, theedge of a target region or organ. Alternatively, the hybrid calibrationcan be applied to the entire image, thus creating a new calibrated imagewhere all image voxels are calibrated to the hybrid reference in a step123.

After the image is calibrated, the target tissue or detail to beanalyzed is next located in a step 124. The target tissue may be locatedby search algorithms which make use of location, density and shape ofthe targets. In one embodiment, the target tissue is located by usingthe known phantom location to set a search ROI in which a more detailedsearch occurs. Lung calcifications can be found by prior art methods,such as described in U.S. Pat. No. 4,922,915, cited above. Using thelocation of the vertebral body, the abdominal aorta can be locatedwithin an ROI which includes the aorta. The measurement ROI may then beplaced around the blood of the aorta and the calcifications in theaorta.

CT images often have streak artifacts, particularly in fast CT scans ofthe heart, which makes it difficult to detect small details such ascalcifications. A low pass filter can be applied to the image in a step125 to reduce the streak artifacts without affecting the target details,such as the small calcifications in this example.

When the target tissue is located and the image calibrated, apre-selected and quantitative threshold is applied or a quantitativethreshold is defined as the edge of a region in a step 126. The edge ofa target or threshold value is located in a step 127 to enablereproducible quantitative measurements of dimensions, volumes or mass ina step 128. FIG. 4A shows a depiction of an image detail, for example, around blood vessel. When the detail is imaged in, for example, a CTscanner, the final image may have 12 or more bits of gray scale values.All of the gray scale values can not be displayed at one time on amonitor, and further, the eye can not see this many gray levels. Theimage is therefore displayed with windows (number of gray levels) andlevels (the central gray level of the window). A variety of windows andlevels are possible in a relatively continuous process. FIG. 4 shows adepiction of an image detail and the voxel intensities across thedetail. A plot across the image would produce the scan line of FIG. 4,showing the scan profile with edges. If the image is displayed on anelectronic monitor or filmed, the perceived location of the edges to theeye will vary with window and level.

FIG. 4 also shows how the apparent location of the detail edges changeswith display level. When the display level is changed from L₁ to L₂, theapparent or measured width (distance) increases from D₁ to D₂. As aresult, if the level is changed, the object appears to get larger andwill be perceived as larger by the observer. If physical measurementsare made of the size or boundaries of the details, they will change,also based on the display settings. If the edge is calibrated asdisclosed herein, and a quantitative edge defined, the detail can bereproducibly measured and displayed.

With a defined quantitative threshold or a defined edge parameter orboth, the boundaries of a target tissue or the number of voxels or boththat meet the threshold criteria can be determined accurately. Thenumber of voxels satisfying the threshold or the extent of the targetdetails can be summed for neighboring CT slices to create a calciumscore which has 3D definition under the quantitative threshold. Thecalibrated image and a defined threshold enable reproducible detectionwithout operator location of details, such as calcifications within theheart or the aorta. Multiple details within a CT slice or the volume canbe analyzed by repeating the steps 110 128, as illustrated by a step129.

Calcifications may be detected and quantified in other parts of thebody, for example, the abdominal aorta. FIG. 7 shows a cross sectionalimage of the abdomen with the reference calibration phantom 5 in place.The abdominal aorta shows a calcified plaque 3. The kidneys 10 and theabdominal muscle 12 are also seen. Bowel gas 3 is also shown atessentially air density. The subcutaneous fat 11 is relativelyhomogeneous and is distributed around the circumference of the body. Thesubcutaneous fat provides a sharp contrast with the surrounding air. Themuscle wall can be segmented out from the fat to define a 360° region ofpurely subcutaneous fat.

The results of the foregoing method are reported as a parameter, such asmass, volume, or a calibrated calcium score in the case of calciumanalysis in the coronary arteries or aorta.

The foregoing calibration procedure can be used with lesser performanceon images without the calibration phantom, or with an alternativephantom made of alternative materials. A variety of plastics simulatingmuscle or fat may be used as the phantom samples. The use of hybridcalibration is therefore not limited to a particular reference phantomor a particular way of being used, i.e., simultaneously scanned versusindependent scanning.

The calibration method of the current disclosure may also be used withsubcutaneous fat or internal air as a calibration reference for thehybrid method. One skilled in the art can see that such alternativemethods fall within the slope of the following claims.

This invention may be embodied in other specific forms without departingfrom the essential characteristics as described herein. The embodimentsdescribed above are to be considered in all respects as illustrativeonly and not restrictive in any manner. The scope of the invention isindicated by the following claims rather than by the foregoingdescription. Any and all changes which come within the meaning and rangeof equivalency of the claims are to be considered within their scope.

1. A method to calibrate a computed tomography image of a subject, themethod comprising: identifying a region of tissue with known propertiesin a CT image of a subject; determining a CT attenuation measure ofvoxels of the known tissue within at least one region of the image ofthe subject; determining a calibration relationship which includes ameasure of CT attenuation in a calibration material and which includes arelationship determined from the CT attenuation measure of the knowntissue related to known properties of the known tissue; and applying thecalibration relationship to the image to create a modified image withimproved properties.
 2. The method of claim 1, wherein the known tissueis muscle or muscle/blood of the subject.
 3. The method of claim 1,wherein the calibration material is scanned independent of a scan of thesubject.
 4. The method of claim 1, wherein the known properties are thefractional components of the tissues.
 5. A method of determining tissuedensities from computed tomography (CT) images, the images containingvoxel representations of x-ray attenuation of a subject's body, themethod comprising: acquiring at least one CT image of the subject'sbody; determining a CT attenuation measure of a calibration material;locating a region of the image containing the subject's muscle tissue;determining a CT attenuation measure of at least one region of the CTimage containing muscle tissue; combining the CT attenuation measure ofthe calibration material and the CT attenuation measure of the at leastone region containing muscle tissue to develop a calibrationrelationship; and applying the calibration relationship to the image ofthe subject's body.
 6. The method of claim 5, wherein the CT attenuationmeasure of the at least one region containing muscle tissue is the modeof a histogram of CT numbers of the region.
 7. The method of claim 5,wherein the calibration material is scanned independent of the subject.8. The method of claim 5, wherein applying the calibration relationshipto the image of the subject's body produces a calibrated imagecontaining voxels expressed in density units.
 9. A method of calibratingand displaying an image of a subject, the image containing gray scalepixel values representative of tissue properties of the subject, themethod comprising: imaging at least one reference material with knownproperties; calibrating the pixel values of the image with pixel valuesof the reference material; defining the image display gray scale inunits of the known properties of the reference materials; and displayingthe images with calibrated gray scales representative of the knownproperties.
 10. The method of claim 9 wherein the known referencematerial is external to the subject.
 11. The method of claim 9 whereinthe known reference material is an internal tissue of the subject. 12.The method of claim 9 wherein the imaging is magnetic resonance imaging.13. The method of claim 9 wherein the display gray scale ranges arecalibrated milligrams per cubic centimeter values for the image voxels.14. The method of claim 9 wherein the calibrated image is made permanenton film or other medium while retaining the calibrated information. 15.The method of claim 9 wherein the calibrated images have display grayscale window and levels which are automatically set based on the knownproperties.